{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "33ff1a8c-0cc5-4739-8bdc-19cef0114425",
   "metadata": {},
   "source": [
    "# **1.1 Olist平台销量前五的商品**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c10a6c72-2b18-4485-9cc4-aba6a48d9e79",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "销量前五的商品类别销售额结果如下：\n",
      "product_category_name_english\n",
      "health_beauty            1263138.54\n",
      "watches_gifts            1206075.33\n",
      "bed_bath_table           1050936.61\n",
      "sports_leisure            993656.51\n",
      "computers_accessories     919640.54\n",
      "Name: price, dtype: float64\n",
      "-------------------分割线-------------------\n",
      "销量前五的商品类别各月份销售额结果如下：\n",
      "product_category_name_english  year_quarter\n",
      "bed_bath_table                 2016Q4             478.99\n",
      "                               2017Q1           41198.82\n",
      "                               2017Q2           91906.82\n",
      "                               2017Q3          176314.88\n",
      "                               2017Q4          190554.60\n",
      "                               2018Q1          203093.29\n",
      "                               2018Q2          221074.47\n",
      "                               2018Q3          126314.74\n",
      "computers_accessories          2016Q4            1399.32\n",
      "                               2017Q1           37452.14\n",
      "                               2017Q2          103025.61\n",
      "                               2017Q3          105599.71\n",
      "                               2017Q4          155360.51\n",
      "                               2018Q1          264784.80\n",
      "                               2018Q2          158548.40\n",
      "                               2018Q3           93470.05\n",
      "health_beauty                  2016Q3             134.97\n",
      "                               2016Q4            4552.51\n",
      "                               2017Q1           57517.69\n",
      "                               2017Q2           98498.48\n",
      "                               2017Q3          134107.61\n",
      "                               2017Q4          185782.12\n",
      "                               2018Q1          248568.51\n",
      "                               2018Q2          292843.65\n",
      "                               2018Q3          241133.00\n",
      "sports_leisure                 2016Q4            3333.64\n",
      "                               2017Q1           50513.62\n",
      "                               2017Q2           91823.79\n",
      "                               2017Q3          128226.44\n",
      "                               2017Q4          177857.57\n",
      "                               2018Q1          248363.35\n",
      "                               2018Q2          178192.32\n",
      "                               2018Q3          115345.78\n",
      "watches_gifts                  2016Q4            3360.24\n",
      "                               2017Q1           42375.06\n",
      "                               2017Q2           90524.96\n",
      "                               2017Q3          114755.55\n",
      "                               2017Q4          235544.62\n",
      "                               2018Q1          231353.16\n",
      "                               2018Q2          307665.20\n",
      "                               2018Q3          180496.54\n",
      "Name: price, dtype: float64\n",
      "--------------------分割线--------------------\n",
      "销量前五商品类别占总销售额的占比：39.80%\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.sans-serif']=['SimHei']#显示中文标签\n",
    "plt.rcParams['axes.unicode_minus']=False\n",
    "df  = pd.read_csv('C:/Users/10528/Desktop/Projects/Brazilian E-Commerce Public Dataset by Olist/olist_orders_dataset.csv')\n",
    "df2 = pd.read_csv('C:/Users/10528/Desktop/Projects/Brazilian E-Commerce Public Dataset by Olist/olist_order_items_dataset.csv')\n",
    "df3 = pd.read_csv('C:/Users/10528/Desktop/Projects/Brazilian E-Commerce Public Dataset by Olist/olist_products_dataset.csv')\n",
    "df4 = pd.read_csv('C:/Users/10528/Desktop/Projects/Brazilian E-Commerce Public Dataset by Olist/product_category_name_translation.csv')\n",
    "df5 = pd.read_csv('C:/Users/10528/Desktop/Projects/Brazilian E-Commerce Public Dataset by Olist/olist_order_reviews_dataset.csv')\n",
    "df = df.merge(df2, on = 'order_id', how = 'left')\n",
    "df = df.merge(df3, on = 'product_id', how = 'left')\n",
    "df = df.merge(df4, on = 'product_category_name', how = 'left')\n",
    "df = df.merge(df5, on = 'order_id', how = 'left')\n",
    "df['shipping_limit_date'] = pd.to_datetime(df['shipping_limit_date'])\n",
    "#分别读取数据并将相关数据汇总到同一张表中\n",
    "the_top5_product_sales = df.groupby(['product_category_name_english'])['price'].sum().sort_values(ascending = False)\n",
    "#根据商品类型英文名进行分类，统计不同类型商品的销售额并按照降序排列\n",
    "top5_products = the_top5_product_sales.head(5)\n",
    "print('销量前五的商品类别销售额结果如下：')\n",
    "print(top5_products)\n",
    "#打印结果\n",
    "print('-------------------分割线-------------------')\n",
    "top5_products = the_top5_product_sales.head(5).index\n",
    "#获取销售额前五的商品类型索引\n",
    "df['year_quarter'] = df['shipping_limit_date'].dt.to_period('Q')\n",
    "#将订单时间跨度转化为年月格式\n",
    "top5_df = df[df['product_category_name_english'].isin(top5_products)]\n",
    "#获取表格中销售额前五的商品类型数据框架\n",
    "top5_rate = (top5_df['price'].sum())/(df['price'].sum())\n",
    "percent = '{:.2%}'.format(top5_rate)\n",
    "#计算销售量前五的商品类型占总营业额的占比\n",
    "result = top5_df.groupby(['product_category_name_english','year_quarter'])['price'].sum().fillna(0)                                                                                  \n",
    "print('销量前五的商品类别各月份销售额结果如下：')\n",
    "print(result)\n",
    "print('--------------------分割线--------------------')\n",
    "print(f'销量前五商品类别占总销售额的占比：{percent}')\n",
    "#打印结果"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25fe8af7-351e-4e28-8a52-8ce9de35864f",
   "metadata": {},
   "source": [
    "**结论：销售额最高的前五类商品类型分别是：健康美妆、钟表礼物、床桌洗浴、运动休闲和电脑配件，总销售额合计占比为40%。对于这些品类，可采取扩张的营销策略，如下所示：**\n",
    "\n",
    "**一、吸引同品类商铺入驻，增加类品种类；**\n",
    "\n",
    "**二、增加广告投入和流量倾斜；**\n",
    "\n",
    "**三、增设打折促销活动，热销商品中打造明星爆品。**\n",
    "\n",
    "**建议：在五类商品中，床桌洗浴是不易复购的品类，其余四类应注重培养用户复购习惯，包括但不限于开设会员充值，积分制度，联系老用户发放优惠券以及定期促销等。**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1509cb0-f824-4d6d-819f-b44538963d4b",
   "metadata": {},
   "source": [
    "## **1.2 销售额下降分析**\n",
    "2018年Q2至Q3季度，五类商品销售额均有下滑，其中，以销售额排名第二的钟表礼物进行数据分析。钟表礼物商品类型在2018Q2至Q3季度销售额显著下滑42%，现在该问题进行拆解。影响销售额变化主要有内部因素和外部因素。外部因素：市场整体规模和市场份额，内部因素：付费用户数和客单价。鉴于暂无巴西所有电商市场数据，因此主要以Olist平台内部因素进行数据分析，并提出四种假设，具体如下："
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7db8c8ba-1e58-4d67-813b-5cd5b2e2eb5a",
   "metadata": {},
   "source": [
    "#### **假设1：用户消费能力下降**\n",
    "销售额与季节性关系：去年同期销售额趋势为连续上升，可排除季节性的影响。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f80f3c64-6367-4fdb-9353-52e61bf2b22c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "钟表礼物各月份客单价如下：\n",
      "year_month\n",
      "2016-10    672.048000\n",
      "2017-01    446.167143\n",
      "2017-02    506.217500\n",
      "2017-03    311.524943\n",
      "2017-04    262.849630\n",
      "2017-05    277.897206\n",
      "2017-06    232.889778\n",
      "2017-07    226.914326\n",
      "2017-08    174.031538\n",
      "2017-09    180.079919\n",
      "2017-10    207.554968\n",
      "2017-11    212.158604\n",
      "2017-12    193.109850\n",
      "2018-01    204.587180\n",
      "2018-02    185.581964\n",
      "2018-03    219.751744\n",
      "2018-04    198.523706\n",
      "2018-05    181.609663\n",
      "2018-06    190.510241\n",
      "2018-07    185.118589\n",
      "2018-08    170.453817\n",
      "2018-09    587.890000\n",
      "Freq: M, Name: price, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "df['year_month'] = df['shipping_limit_date'].dt.to_period('M')\n",
    "#增加订单月度一栏\n",
    "watches_gifts = df[df['product_category_name_english']=='watches_gifts']\n",
    "#获取含钟表礼物的数据框架\n",
    "watches_gifts_average_price = watches_gifts.groupby('year_month')['price'].mean()\n",
    "print('钟表礼物各月份客单价如下：')\n",
    "print(watches_gifts_average_price)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc21aa22-8c79-4f19-ab31-2746d6dbe949",
   "metadata": {},
   "source": [
    "客单价与季节性关系：去年同期客单价（232、226、174）与今年客单价（190、185、170）均为三连降趋势，因此客单价具有季节性。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "94dc5735-7401-4e9c-b8cd-371a7f53ef7b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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v3w6dTletMuj1erz++useexq6d++O4uJirF27FitXrsS5c+dQXl6O+Ph4mEwmt5/ho48+irvvvhvx8fEoKCiQ3l+j0SA8PFzqiXB5+eWX8csvv0jPX3jhBZjNZhw4cABFRUXSl4DLRUZGuj1/4YUXpN+94uJizJ07FwEBAW7HzJgxA35+fpVedvX2229j5syZFbZfvHgRzZs3h8Viwblz5zyWBwAiIiI8bif5YVBTvXM4HJg6dSqio6Mxa9YsAM7gdAWqi1ardet6vpoZM2YgLCwMCxYsgBACS5YswZAhQ/DLL79IXcMuV76XJxqNxuN2ccWiFgqFwuNCF9u2bcOKFSuwdOlS6Y9lXl4epk6digEDBuDo0aMYM2aM25cF1/kAYPz48fjuu++QnJyM1atXuw0blJWVISAgQArg0tJSAKjQ49CsWTOPn2H//v346quvcOjQIaSlpeHpp59GaGgotFptZdXhZtCgQUhJSUFAQIDUHb5t2zaMHTsWb7/9NsxmM0aOHCkFlNFohFqtRnl5uVu9lpeXY8aMGVixYgUiIiKQnp6OCRMm4Oeff8aNN95YZRlat24tffFy+eWXX7B161Y89thj+PrrrxESEoIRI0bg22+/hY+PD2688UYYjUb4+PhIr0lNTUVubi4AZ8ip1WqEh4dDqVQiJycHY8aMcXuPpKQkt9+nNm3aAHB2XwcGBqKwsFDa9/PPP0uX2Pn5+UEIIV2aZTabodfr0blzZ3Tu3NnjZ1Sr1di2bRsGDRrktv3mm2/2+Ptpt9sxdOhQTJgwAXPnzsVzzz2Hfv364e6778acOXPQunVrzJ8/v0LXO8kbg5rq3WuvvYa9e/di9+7d0h/MZs2aISMjw+24/Pz8Cq3Xyvz2229Yv349Lly4IIXTvffei5iYGLz77rtYsGABSktLoVQqodForto6d7HZbFK4uLq0S0pKADjDLj8/HyUlJRVaLTk5OZg6dSruvPNOtwU7wsLC3BZZWb9+PQDnlxKFQoFDhw5hwoQJ6NKlC+bMmQMAuOGGG/Dqq6+6nb+oqAjNmzcHAGRnZyMgIABGo9FjK7akpKRCPQYEBKB169ZISUlBVlYW4uPj4e/vj6ysLBw4cMDtPJ7O6efnBz8/P+n5t99+i8mTJ+Oxxx7DjBkzMGzYMOTk5GDBggWw2Wy49957UVRUhG3btkl1tWPHDsyaNQvZ2dl49tlnsWrVKowePRpvvfUWRo8e7TYO7ElxcTESEhJw8OBB7Nq1C+fOncOGDRtw77334siRI3j77bexfPlyqNVqrF+/Hv369YNarYbJZHIL6s6dO8NgMAAAevfuDbPZjPfffx8RERHw8/PDtGnT3N53zZo10lDD5Ww2G4qKiiqM4+t0OoSFhUnPy8vLIYTAlClTsGrVqio/Y1W/p56C+sMPP8SZM2cwadIkaVtGRoY0H4QaqHqevEZN3Pbt24VKpRKLFi1y2z5+/HgxevRot23jxo0Tw4cPr3COKVOmVJix+sUXX4jg4OAKx3bp0kWMGzdOCCFEr169BAChUCiEVqsVOp3O7YFLs64v36bRaIRCoRCffvqpSEpKEgDE22+/LYQQYvLkyaJ3794iODjYrew2m00MGTJEREdHV7iERggh8vLyRHZ2tigoKHB7pKWlCbVaLWbMmFFhX1ZWligtLZXOsWTJEjFo0CAhhBDh4eHC19e3wvW6ISEhAoCYOHFipT+PV1991W1W9b///W/Rs2dPj5dntWrVSqxatcrt9a7LsVQqldBoNOLTTz8VQgixbds2odfrxZEjR8SYMWNEeHi42L59u/Q6u90uxo8fL3r27CnS0tLEV199JSIiIoQQQiQlJYlXXnlFWCyWKmd9nzt3TqjVahETEyOee+45ERERIVauXCmMRqNo06aNuOuuu4TD4RCZmZnCx8dHfPHFF0IIIQICAsTq1avdzpWamlrhMqoNGzZ4nDU9b948j9e77969W8ybN6/S6/IvfxQXF4uSkpIK5wAgzXgXwnklgkajqfC7qlAoKlyhkJOTI4KDg8W8efPc6giAOHDggBBCiJiYGOlnRA0Hg5rqzYkTJ0RwcLAYNWpUhUU0vvrqK6HVasWxY8eEEM4/nHq93u0aZhdPQb1161YBwG0RijNnzgi1Wi2efPJJIYTzOlO73V5p+Sq7PMvhcAi73S4cDodo3ry5GDlypBDCuUALLl0S9N///lc6/pFHHhFarVbs27fP4/tMmTKlwmU8rgcAoVQqPW5ft26ddI4ZM2aISZMmSc/LyspEu3btxNKlS6Vt8+fPF9HR0RUui7rc5UF98eJF8dlnn0l/6F0Lnrj84x//kMK2vLxcLF26VERHR4vmzZuLHTt2uIWA2WwWU6dOFVqtVsTHx7tdP315mV3Xdl8e1Je7MqitVqvbz/CXX34RNptNCCHcFjzJzMwUeXl5Qgghpk2bJm688Ubp8jSlUim++uort/e5PKjz8/PdPv+VIalSqTwG9cyZM6u98MuJEyc8/DQ8B/XOnTsrHNejR48Kv6uTJk0SMTExbl/o/vnPf4qWLVtK/79dGdRlZWUey0Hywq5vqhdWqxVjxoyBQqHArFmz3Lo1Y2Njcc899+Dmm2/GoEGDMHLkSGzZsgXh4eF4+OGHq3X+3r17o1mzZrj99ttx3333wWKx4KuvvoJSqZS6nisbc74a15KLgHOG7xNPPIFnn30WQ4YMQWhoKEpKSjB16lQAwGeffYZly5bhscceg1qtRkJCAgBn96drHPKjjz7CypUrPXYpVzYmeeWlNjt37nSbSKTX67F69WoMHToUzZs3h8lkwmuvvYbt27dX2e3pcDhgt9sxY8YM5OTkVJg4dbk333zT7fm3336Lu+66C4sWLXKbCLhnzx5MmzYNq1evxvHjx5Gbm4sTJ06gdevWUKv/+pNzZRdxZS7/7CdPnsQ999yDNWvW4NZbb5VmSl/JNVFqzZo1WLFiBbZt2wa1Wo2SkhI4HA63bvvLvffee1i+fLm0vnpMTEyF9bVfeuklt6VGXYKCgnD77be7XVJ4pcTERHTu3Lnanx0Abr/99gq/K1fO2F6/fj0+++wzfPPNN1I3/tatW/Hmm29i6dKlHn/XiouL0bJlS6xZswZ33313tctDXuDtbwrUNPz222+Vti5cLYOSkhLxz3/+U3Tr1k1MnDjRbYGPy3lqUQshxOnTp8U999wjIiMjhVarFZ07dxbfffddtcsYFBQkVqxYcdXjXnvtNREVFSX0er3o3r27ACAtSfn//t//8/gZK1t44nJ2u10olUrx888/V3lcYmKiACASExMr7Fu6dKm0sMbly0tWZuzYsQKACA8Pd1tWUwghvv/++yqXEL1ye0hIiOjYsaNQKBRi5MiR4ty5c8JkMom//e1vQqFQiKCgIDFs2DDxySefVDhXZS3qJ598UoSGhorffvtNnD59WsycOVMoFIoKy3cKIUTr1q2l3yW73S6WLFkilEqlmD9/vnTMnj17BABx8OBBt9du2rRJABCtW7cWu3btEkI4V7C78ueWn58vJk2aJIYOHVrh/V966SUxaNCgKru8Dx48KAC4LfzjYrPZBACpV8lVp55a1IMHD3ZrUf/000/ikUceEUI4lyJdsGCB0Gg0bgvtCOHsdXj00UfFqVOnxLJlyyoskkPyxKAmusTX11d89NFH1/y6Dz/88Lrf+8knnxR9+/YVAMSpU6eqPPahhx4S3bp1E2azWZw+fVps3rxZLFy4UNx+++3C399fjBs3TgwcOFBoNBpxyy23iEceeUS8+OKL4u2333brBrfb7SIyMlJER0eLP/74o8L7fPPNNwJAhWVcPblw4YLQ6/Wibdu2YseOHRX2nzp1Sjz11FOiTZs2Yu/evRX2f/TRRyI0NLTC9p9++kkEBwdLX3h0Op2YNWuWxzKEhoaKjz76SNjtdjFs2DChUCikbvwXX3xRtGnTRvj4+Ig2bdpUWMJz//79Yvjw4VK3txBCfPnll25BXV5eLtq2bSv8/Pzchhhc5syZU+2ub09fNAoLCwUAkZCQIG0LCAioENSbN28WLVq08DjWXFpaKtq2bSs0Go14+eWXK3yZmj9/voiJiRGBgYGiWbNmldYlyQuDmugSrVYr3nnnHa+895o1a8S8efPE5s2br3rsoUOHxObNm0VZWZno0aOH6Natm3j44YfFZ5995jYZKiMjQ3zyySdixowZom/fvh7HVXfs2OGxdSeEc4IerphgVZWdO3d6nCBVHQsWLBC+vr41eq2LVquVlnJNSUkR33//vbTvt99+Ew8//LBYvnx5heU/r0VmZmal63TPnDnzqjdVOX78eKVj1BcvXhSBgYFurX2dTlchqJ955hnRr18/cf78eY/vsXfv3kp/ptQwKYTwcAEoERFdk+LiYjgcjgoLlxBdLwY1ERGRjHGtbyIiIhljUBMREckYg5qIiEjGmkxQCyFgNBo93jyBiIhIrppMUJtMJgQGBkq3KiQiImoImkxQExERNUQMaiIiIhljUBMREckYg5qIiEjGGNREREQyxqAmIiKSMQY1ERGRjDGoiYiIZIxBTUREJGMMaiIiIhljUBMREckYg5qIiEjGGNREREQyxqAmIiKSMQY1ERGRjDGoiYiIZIxBTUREJGMMaiIiIhljUBMREckYg5qIiEjG1N4uQFN054hRyMrJ9bgvIjwMmzaur+cSERGRXDGovSArJxcPzl/pcd+nc6fWc2mIiEjO2PVNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMa8EtTr169HXFwc1Go1evXqhZMnTwIAEhMT0bNnTwQHB2P27NkQQkivqWofERFRY1XvQZ2SkoKpU6di0aJFuHDhAmJiYjBt2jRYLBaMHDkSPXr0QEJCApKSkrBq1SoAqHIfERFRY1bvQX3y5EksWLAA48aNQ0REBGbMmIGEhARs2rQJRUVFWLJkCeLj47FgwQIsX74cAKrcR0RE1Jip6/sNR4wY4fb8jz/+QJs2bXD06FH07t0bPj4+AIAuXbogKSkJAKrcVxmLxQKLxSI9NxqNtfkxiIiI6oVXJ5OVl5dj8eLFmDlzJoxGI2JjY6V9CoUCKpUKBQUFVe6rzMKFCxEYGCg9WrZsWaefhYiIqC54Najnzp0LPz8/PPLII1Cr1dDpdG779Xo9SktLq9xXmTlz5qCoqEh6pKen18lnICIiqkv13vXtsnXrVnzwwQfYv38/NBoNQkJCkJiY6HaMyWSCVqutcl9ldDpdhXAnIiJqaLzSoj5z5gwmTZqEpUuXokOHDgCAnj17Yv/+/dIxaWlpsFgsCAkJqXIfERFRY1bvQV1WVoYRI0bgnnvuwahRo1BcXIzi4mL0798fRUVFWL16NQBg0aJFGDJkCFQqFQYMGFDpPiIiosas3ru+N2/ejJMnT+LkyZP46KOPpO2pqalYtmwZJk6ciNmzZ8Nut2PXrl3OQqrVle4jIiJqzOo9qO+5555KVxVr3bo1kpOTkZCQgD59+iA8PNztdZXtIyIiaqy8NpmsMlFRUYiKirrmfURERI0Rb8pBREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCYiIpIxBjUREZGMMaiJiIhkjEFNREQkYwxqIiIiGWNQExERyZja2wWg2nPniFHIysn1uC8iPAybNq6v5xIREdH1YlA3Ilk5uXhw/kqP+z6dO7WeS0NERLWBXd9EREQyxqAmIiKSMQY1ERGRjDGoiYiIZIxBTUREJGMMaiIiIhljUBMREckYg5qIiEjGGNREREQyxqAmIiKSMQY1ERGRjDGoiYiIZIxBTUREJGMMaiIiIhnjbS5lJiUlBd179fW4j/eUJiJqehjUMmNzOHhPaSIikrDrm4iISMa8FtR5eXmIjY1FWlqatO3xxx+HQqGQHm3atJH2JSYmomfPnggODsbs2bMhhPBCqYmIiOqXV4I6NzcXI0aMcAtpADh8+DB++OEHFBQUoKCgAL///jsAwGKxYOTIkejRowcSEhKQlJSEVatW1X/BiYiI6plXgnrChAmYMGGC2zabzYbExEQMGDAAQUFBCAoKgr+/PwBg06ZNKCoqwpIlSxAfH48FCxZg+fLl3ig6ERFRvfJKUC9btgyzZs1y23bs2DEIIdC1a1cYDAYMHz4c586dAwAcPXoUvXv3ho+PDwCgS5cuSEpKqvI9LBYLjEaj24OIiKih8UpQx8XFVdh28uRJdOzYEV988QWSkpKg0Wgwffp0AIDRaERsbKx0rEKhgEqlQkFBQaXvsXDhQgQGBkqPli1b1v4HISIiqmOymfU9adIk7N+/Hz179kRsbCzeffddbNmyBUajEWq1Gjqdzu14vV6P0tLSSs83Z84cFBUVSY/09PS6/ghERES1TrbXUQcFBcHhcODixYsICQlBYmKi236TyQStVlvp63U6XYVwJyIiamhk06J+6qmnsHbtWun5oUOHoFQq0bJlS/Ts2RP79++X9qWlpcFisSAkJMQbRSUiIqo3smlRd+3aFS+88AIiIyNhs9nw+OOP46GHHoKPjw8GDBiAoqIirF69GpMnT8aiRYswZMgQqFQqbxebiIioTskmqCdPnoyTJ09i1KhR8Pf3x+jRo7FgwQIAgFqtxrJlyzBx4kTMnj0bdrsdu3bt8nKJiYiI6p5Xg/rK1cUWLlyIhQsXejz2nnvuQXJyMhISEtCnTx+Eh4fXRxGJiIi8SjYt6uqIiopCVFSUt4tBRERUb2QzmYyIiIgqYlATERHJGIOaiIhIxhjUREREMsagJiIikrEGNeub6s6dI0YhKyfX476I8DBs2ri+nktEREQAg5ouycrJxYPzV3rc9+ncqfVcGiIicmHXNxERkYwxqImIiGSMQU1ERCRjDGoiIiIZY1ATERHJGIOaiIhIxhjUREREMsagJiIikjEGNRERkYwxqImIiGSMQU1ERCRjDOoGwGp34PdzBShpOxx///w3vP/zn8gsMnu7WEREVA94Uw6ZS8srwc5T2TCabUBUd2w8dhEbj13E4s1/YGKvVph7dwfoNSpvF5OIiOoIW9QylpJTjPVHMmA02+CnU0OftgfP3XkjbokNgUMAa/afw+j3f8W5vFJvF5WIiOoIg1qm8oot2HwiEwBwY6Q/HuwdA5/U3Xh0YDzWTr8Vn/7tFoT6anHyohH3f7QfF4vKvFxiIiKqCwxqGbLZHdh47CKsdoGoIAOGtI+AVu3+o+p/Qzh+eKI/4sJ8caGwDA98fAAOjcFLJSYiorrCoJah4xeKUFhmha9Ohbs6R0KlVHg8LjJQj0+n9ULzQD1SckpQ3OEeCCHqubRERFSXGNRyo9bhUFoBAKB3bCh8tFXP94sKMmD1/90Cg0YFW0gsDp0tqI9SEhFRPWFQy4xPpyEos9oRaNCgffOAar3mhgh//GtURwDA/jN5yCjkeDURUWPBoJYRm90BQ5fhAIDecSGVdnl7MqZHNLSZxyEEsP1UNuwOdoETETUGDGoZSckpgVLvB3+9Gm0j/K/ptQqFAj7JW2HQqJBfUo7D59gFTkTUGDCoZeRkphEA0D4yAEpF9VvTLkqbGQPahgEADqbmo6jMWqvlIyKi+lejoH7ggQcq3ffvf/+7xoVpyootNmnhkvbNr601fbl2Ef5oGWyA3SGw98/c2ioeERF5SY2COikpCWVlZSgoKEBRUREKCwvx/fffo7y8HD/88ENtl7FJ+CPTBAHAmnkaQT7aGp9HoVCg/w3hAIDk7GKuCU5E1MBVK6jVajX8/f1hMBgwb948BAcHY+XKlYiMjERoaCgeeOABLFy4EHa7HTqdrq7L3CidvOjs9jaf3nvd5wr310mt8j1/5vLaaiKiBqxaQd2vXz9069YN27dvh8PhgErlvAnE2rVrceutt6Jbt27QaDQwGLgyVk0UlVmRV1IOhQKwnDlUK+fsHRcKlVKBC4VlOJvPtcCJiBqqagW14tLEJrW64uIbihpMeiJ3aXklAIAWgQaI8tq5BjpAr0GX6EAAzollbFMTETVM1zXrOyMjA2VlZcjPz0dZWRlOnz4Ni8VSW2VrMs5emkQWE+pTq+ft3ioYKoUCF4vMsAW1qtVzExFR/ajx/aiFEFi8eDFyc3Nx/vx5lJSUYPz48bh48WJtlq9BunPEKGTlVD7j+kxqqvTfNrsD6Ze6pluH+tZqOfx0anRoEYDjF4pQFtOnVs9NRET1o8ZBrVAo8Oabb2Lx4sUYNGgQdu3ahd27d2Pw4MG1Wb4GKSsnFw/OX1np/rnj+0n/faGwDDaHgK9OhTC/ms/2rkyPmGAkZhTBFhKHY+cL0SU6qNbfg4iI6s51L3iiUCg4Tn0d0lzd3iG+dVKPgQaNtMrZqr1ptX5+IiKqW9UK6qysLOTk5GDz5s1u2w8cOID8/HwUFhYCAC8DqgHXIieta3l8+nJdWwYBADYcy0C2iddVExE1JNUK6q5du6JPnz5ISUlB586dUVJSgsjISBw4cADNmzeHVqtFeXk5srOz67q8jUpZuR35peUAgOjgugvqyAA9VEXnYbULfHEgvc7eh4iIal+1xqg///xzt+f/+te/cO+99+Lee++Vtp09exYhISEwGo21W8JG7GKR81KsYB8NDFpVnb6X/nwCSgKjsebAWcwYFA+tmsu8ExE1BDX6az1+/PgK22JiYqDRaPDxxx9fd6GaioxLy3u2CKr7hWK0OafQzF+HHJMF205m1fn7ERFR7ahRUL/44ouV7uvWrVuNC9PUZBQ6W9TNA/V1/l4K4cCYHtEAgP8dYvc3EVFDUSv9n2azGVFRUbVxqibD5nAg2+RcHKY+WtQAMO7mlgCA3ck50pcEIiKSt2u6jnr9+vUVVh7z9/fH8OHDOZHsGmUbLbA7BAwaFYIMmnp5z9ZhvugdF4L9Z/LxVcJ5zBpyQ728LxER1dw1BfW0adPQqVMnHDhwAL169QIAXLhwAadPn/a4DjhVLuPSRLIWQfp6vQ59fM+W2H8mH2sT0vH4bW2gVPIaeCIiObtq13d6ejpGjhyJP//8EwqFAjt37kRERAR27tyJnTt31kcZG6WLhc6JZM0D6/eOY3d2ag5/vRoXCstwMC2/Xt+biIiu3VWDurS0FDqdDt26dZMWNqHrl2VyBXXdTyS7nF6jwp2dIgEA3x/NqNf3JiKia3fVoG7Xrh2+/vprJCcnw9fXF7t374bZbMYvv/yCXbt2oaysDLt374bD4cDu3buxZcuW+ih3g6YwBKDEYgcAhPvr6v39R3V1Tvz78fhFlNsc9f7+RERUfdUeWI6MjIRarcazzz6LgoIC/POf/wQA5OXl4dlnn4XdbsczzzyDkpISnDhxos4K3BhowmIAACE+WmhU9b/wSO+4UIRfuqb6l+Qc3N4+ot7LQERE1VOtoD537hx27doFhUKBffv2ITY2Fvv27QMAtG3bFvv27YPBYMDBgwfrtLCNhfpSUIcH1F9rOiUlBd179ZWel7QZArS8BTNeWwW/k9+73XqTiIjk46pBfezYMdx222149NFH66M8TYIrqJv51V9Q2xwOt1tvZhrN+N+hdDhadMaECaPwysQB9VYWIiKqvqsGdadOnbB37160a9cOH374IVavXo3i4mKsXr2ad8uqIXXopRa1F8anXSL8dQjQq2E023D20h28iIhIfq4a1EqlEu3atQMA3Hnnndi4cSNuv/12bNq0CXa7HUOGDAEA3pO6msxWO1QB4QCAZl4MaoVCgTbN/PDbuUKk5BR7rRxERFS1a1qlZPXq1R63OxwOWK3WWilQY5dzadnQQIMGOk3d3jHrauLDnUF9JrcEUHq3LERE5Fm1phw7HA5s3Lix0v0KhQI///xzbZWpUXOt7+3Nbm+X5oF6+GhVKLc5oGnR3tvFISIiD6od1Pfff3+l+xUKBfr27VvpfvpL9qWFTrzZ7e2iUCgQH+4HANDF9vByaYiIyJNqBbVarYZGUz83jmjs8orLAQBh9Tjjuyrx4b4AAF3r7pwcSEQkQ9Ueo7ZarZWOUbvodDrccccdCA4Ovu6CNUZ2h0BBqTOoQ/20Xi6NU3SwD7QqJcoNAcgyWhBZz0uaEhFR1a4pqH/66acqW12HDx/GV199ha+//rpWCtfYFJaWwyEAR3kZ/HXyuNuYSqlATKgPkrOLkZpbwqAmIpKZaqeFv78/Pv/88yqP+fTTT/Hcc89dd6Eaq7wSZ2vaXnABCkUXL5fmL63DfJ1BnVeCW+NDvV0cIiK6TLUXmq7OddIdOnTAypUrr3pcU+UKaluBvO5a1TrUB0I4kGOyoNhs83ZxiIjoMtVqUQshUF5eXun+9PR02Gw29OjBmcNVySt2Xpplzz/v5ZK489GqYctOhSYiHml5JegUFejtIhER0SXValHbbDbcddddle5fv349hg0bhqKiolorWGOUL7WoL3i5JBWVnzsKAEjNLfFySYiI6HLVCmqNRoMPP/wQX375JQCgrKwMNpsNDocDDocDM2fOxLBhwzB27FjYbOw69cRmd6Cw1Ll6mz1fjkF9DACQXlAKu4OXaRERyUW1ur5NJhOGDRsGjUaDCRMmoFWrVsjPz3c7xjUb/O9//zs++OCD2i9pA1dQaoUAoFMr4SiTX8+DLe8cDBoVyqx2XCwqQ3Swj7eLREREqGZQv/TSS1CpVPjxxx+lbZ7GrE+fPl17JWtk8kqc49OhflrIa4TaRaBViA/+yDLhXH4pg5qISCaqFdTz588HAPj6OlexcjgcUCqVFWaCt2/P9aIr41qRLNRXHiuSedIq1BnUZ/NK0Sfe26UhIiKgmkHtCmiXZcuW1UlhGjPXRLIQX3msSOZJqxBnKzrbZEGZ1Q6Dl+/uRURE13Ad9eXuu+8+3n/6GrmWDg32ke+a6X46NUIvfZFIzy/1cmmIiAioYVDTtXE4BIrKnDO+g2Xcogac3d8AcI5BTUQkCwzqelBktsIhALVSIZs1vivj6v5mUBMRyQODuh4UlLi6vbWyHzJoEWiAUgGYzDYYL/UCEBGR9zCo60HBpYVO5Dw+7aJVKxER4LyD1vnCMi+XhoiIGNT1wDWRLEjm49MuUUEGAMD5AnZ/ExF5G4O6HjSEGd+Xiw52BvWFAraoiYi8jUFdDwpKXF3fDaNF3TzQAIUCMHKcmojI6xjUdcxitaPMagfQcIJaq1Yiwt85Tn2B49RERF7ltaDOy8tDbGws0tLSpG2JiYno2bMngoODMXv2bOlGH1fbJ2euiWR+OjW06obzvSgq2DVOzaAmIvImryRHbm4uRowY4RbSFosFI0eORI8ePZCQkICkpCSsWrXqqvvkTppI1kDGp12igzmhjIhIDrwS1BMmTMCECRPctm3atAlFRUVYsmQJ4uPjsWDBAixfvvyq++Tur4lkDaPb26XFZePUdl2At4tDRNRkeSWoly1bhlmzZrltO3r0KHr37g0fH+fKWF26dEFSUtJV91XGYrHAaDS6Pbyh8FLXd0NrUWvVSjTzd97pyxbUysulISJquryynmVcXFyFbUajEbGxsdJzhUIBlUqFgoKCKvcFBwd7fI+FCxfilVdeqf3CX6PCsoYZ1AAQHeyDLKMF+apgdO/V1+MxEeFh2LRxfT2XjIio6ZDNwtNqtRo6nfu9mvV6PUpLS6vcV1lQz5kzB0899ZT03Gg0omXLlrVf8CoIIVDkalEbGlbXNwBEBxlw+GwB1M3b4cGZ/+fxmE/nTq3nUhERNS2ymYYcEhKCnJwct20mkwlarbbKfZXR6XQICAhwe9S3Mqsd5XYHACDAIJvvRNXWPEgPhQJQBTSDyczrqYmIvEE2Qd2zZ0/s379fep6WlgaLxYKQkJAq98mZa3zaX6+GWimbqq42nVoljVNzlTIiIu+QTXoMGDAARUVFWL16NQBg0aJFGDJkCFQqVZX75EwanzY0vPFpl+gg5wQ+3qCDiMg7ZNMfq1arsWzZMkycOBGzZ8+G3W7Hrl27rrpPzlzj04ENcCKZS4tgPQ6fAzIY1EREXuHVoL5ydbF77rkHycnJSEhIQJ8+fRAeHl6tfXJVWHZpsZMGOJHMpXmgc+GTglIryqx2GDTy7sUgImpsZNOidomKikJUVNQ175OjhnoN9eUMGhVsBRlQB7fAxaIyxIX5ebtIRERNimzGqBsbIYQ0Rh3YgMeoAcCa9ScA4GKh2cslISJqehjUdcRsdaDc5rw0qyFPJgMAmyuoixjURET1jUFdR1zj0346NdSqhl3N1sxkAECm0Qy7o2HctYyIqLFo2AkiY3+tSNawW9MAYC/KhF6thN0hkGOyeLs4RERNCoO6jkjj0w14Itnlmgc5Z39nFPEyLSKi+sSgriPGS0Ed0Aha1ADQPFAPgOPURET1jUFdR4pcLWp94wjqFpeup75YWFbh+nciIqo7DOo6YjTbADT8S7NcIgJ0UCqAknI7TJc+GxER1T0GdR0QShWKLc4wa4h3zfJErVIi/NINOjhOTURUfxjUdcChCwQAaFSKRrXk5l/d3xynJiKqLwzqOmA3BAFwTiRTKBTeLUwtck0oY4uaiKj+MKjrgEMfBKDxTCRzcV2ilVdcDovN7uXSEBE1DQzqOuC4rEXdmPjp1AjQqyEAZPIyLSKiesGgrgN2V4u6kQU18FermtdTExHVDwZ1HfirRd04ZnxfrnmAc5yaLWoiovrBoK4DjXWMGrhshTKjmQufEBHVAwZ1LSsqtUJonGHW2MaoASDMTwe1UoFymwP5JeXeLg4RUaPHoK5l5/JLAQA+WhU0Dfz2lp4olQpEBPzVqiYiorrV+JLEy9ILnEEd0Ai7vV1c3d8cpyYiqnsM6lrmalE3xhnfLryTFhFR/WFQ17L0S0HdGGd8u0ReCur8knI41Dovl4aIqHFjUNeyptCi9tGqpc9nC2jh5dIQETVuDOpadr7AuQ52Yx6jBv5qVdsDorxcEiKixo1BXYvsDoELl4K6Mbeogb8WPrExqImI6lTjHUj1giyjGeV2B+Cww09f+1WbkpKC7r36Vrr/TGpqrb9nZVwTymwBUXA4BJTKxnOXMCIiOWFQ1yLXRDKluQjKOri9pc3hwIPzV1a6f+74frX+npVxLXxi0+iRklOMGyL86+29iYiaEnZ916JzlwV1Y3f5wie/nSvwcmmIiBovBnUtSr80Pq0yF3q3IPXE1f3929lC7xaEiKgRY1DXIqnru6zQuwWpJ1JQs0VNRFRnGNS16K8x6kLvFqSeuC7RSs4uRlGZ1culISJqnBjUtcg1Rq1qIi1qH60aytJ8AMCR9ELvFoaIqJFiUNcSs9WObJMFQNNpUQOA2pgBAPjtLLu/iYjqAoO6lrhWJPPTqaGwlnm5NPVHbbwAgOPURER1hUFdS1zj09HBBjSlpT/URecBOLu+HQ7h5dIQETU+DOpa4roPdasQHy+XpH6pSrJh0KhgMtuQklPs7eIQETU6DOpaci7PGdQtm1hQK4RAl+hAAOz+JiKqCwzqWtJUW9QA0D0mGAAXPiEiqgsM6lpyLt85gaxliMHLJal/3VtdCmq2qImIah2DuhYIIXD+0mSylsFNr0XdrVUQAC58QkRUFxjUtaCw1AqTxQYAiG6CQR3mp0NMqPNzc+ETIqLaxaCuBa7x6XB/HQxalZdL4x3dWgYB4MInRES1jUFdC1xLhzbFiWQu0oQyjlMTEdUqBnUtSHdNJAtuehPJXFwTyrjwCRFR7WJQ14KmfGmWy42R/tLCJ39y4RMiolrDoK4F0vKhTTio1SqltPDJ7+z+JiKqNQzqWpDOMWoAXPiEiKguMKivk90hcKHQtdhJEw9qLnxCRFTrGNTXKdNohtUuoFEpEBmg93ZxvIoLnxAR1T4G9XVy3YwjKsgAlbIp3eCyIi58QkRU+xjU18k147upd3u7cOETIqLaxaC+TpxI5o4LnxAR1S4G9XXiqmTuuPAJEVHtYlBfJwa1Oy58QkRUuxjU18nV9c0xaqfLFz7hODUR0fVjUF+HEosNucXlAIBWoQxqF45TExHVHgb1dXDN+A7y0SBAr/FyaeTDNU79+7lC7xaEiKgRYFBfB9c11ByfdseFT4iIag+D+jqc4/i0R2F+OrS+NBTAcWoiouvDoL4OvIa6crfEhgAA9qfmebkkREQNG4P6OvDSrMrdEhsKADiYmu/lkhARNWwM6uvAoK5cr0st6uPni1BabvNyaYiIGi4GdQ05HALpBc7bWzKoK4oONqBFoB42h+D9qYmIrgODuoayTRaU2xxQKRVoHti0b2/piUKhkMapD3KcmoioxhjUNeTq9o4KMkCtYjV60ivOOU59gOPUREQ1xoSpIY5PX52rRf17eiHMVruXS0NE1DAxqGuI11BfXVyYL8L8dCi3OXDsfJG3i0NE1CAxqGuI11BfnUKhkGZ/c5yaiKhmGNQ1xK7v6nF1f3OcmoioZhjUNcSgrh5XUB8+WwCr3eHl0hARNTwM6hooK7cjx2QBwKC+mnYR/gg0aFBabseJDKO3i0NE1OAwqGvAdXvLAL0agT68vWVVlEoFera+1P19huPURETXikFdA9LtLUPZmq6OvyaUcZyaiOhaMahrgOPT16ZX3KWgTsuH3SG8XBoiooaFQV0DvIb62nRoHgB/nRomsw0nMng9NRHRtWBQ1wCvob42apVSWk50758cpyYiuhYM6hpg1/e169vGFdS5Xi4JEVHDwqC+RkIIBnUN9GsTBgA4lJbPdb+JiK4Bg/oa5ZgssNgcUCqAFkEGbxenwWjTzA/N/HWw2Bz47WyBt4tDRNRgyC6oH3/8cSgUCunRpk0bAEBiYiJ69uyJ4OBgzJ49G0J4Z/awyWLDTdGB6NAiABre3rLaFAoF+l5qVe9NYfc3EVF1yS5pDh8+jB9++AEFBQUoKCjA77//DovFgpEjR6JHjx5ISEhAUlISVq1a5ZXyxYf7Yf3f+2Hj4/298v4NWZ945zj1Hk4oIyKqNlkFtc1mQ2JiIgYMGICgoCAEBQXB398fmzZtQlFREZYsWYL4+HgsWLAAy5cv93Zx6Rr1u8HZoj5+vhCFpeVeLg0RUcMgq6A+duwYhBDo2rUrDAYDhg8fjnPnzuHo0aPo3bs3fHyck7e6dOmCpKSkKs9lsVhgNBrdHuRdzQMNaBvhB4cA9nD2NxFRtcgqqE+ePImOHTviiy++QFJSEjQaDaZPnw6j0YjY2FjpOIVCAZVKhYKCyiclLVy4EIGBgdKjZcuW9fER6CoGtg0HAOz6I8fLJSEiahhkFdSTJk3C/v370bNnT8TGxuLdd9/Fli1b4HA4oNPp3I7V6/UoLS2t9Fxz5sxBUVGR9EhPT6/r4lM1DGzbDACw63SO1yYEEhE1JLIK6isFBQXB4XAgMjISOTnuLTCTyQStVlvpa3U6HQICAtwe5H03tw6GQaNCtsmCU5kmbxeHiEj2ZBXUTz31FNauXSs9P3ToEJRKJTp37oz9+/dL29PS0mCxWBASEuKNYtJ10GtUuPXS7O9dp9n9TUR0NbIK6q5du+KFF17A7t27sWPHDjz++ON46KGHcMcdd6CoqAirV68GACxatAhDhgyBSqXycompJlzj1D//ke3lkhARyZ/a2wW43OTJk3Hy5EmMGjUK/v7+GD16NBYsWAC1Wo1ly5Zh4sSJmD17Nux2O3bt2uXt4lINDWrnDOqEtAIYzVYE6DVeLhERkXzJKqgB52zthQsXVth+zz33IDk5GQkJCejTpw/Cw8O9UDqqDTGhvogP90VKTgl2/ZGDkTe18HaRiIhkS1Zd31cTFRWFUaNGMaQbgSHtIwAA209mebkkRETy1qCCmhqPIR2cQb3zjxzY7A4vl4aISL5k1/VNDUtKSgq69+pb6f6I8DBs2ri+wvburYIR7KNBQakVCWcL0DsutC6LSUTUYDGo6brYHA48OH9lpfs/nTvV43aVUoHB7Zrh298vYPvJLAY1EVEl2PVNXnP7pXHqrUlZXKWMiKgSDGrymoHtwqFTK5GWV8pVyoiIKsGgJq/x06kx4NLiJ5uOX/RyaYiI5IlBTV51V+dIAMCPiZleLgkRkTwxqMmrbm8fAY1KgT+zi5Gcxe5vIqIrMajJqwL0GvRrEwYA2MRWNRFRBQxq8ro7OzcHAGw8luHlkhARyQ+DmrxuWMdIaFVKnM4qxsmLRm8Xh4hIVhjU5HWBBg0G3+ic/b3+CFvVRESXY1CTLNzTNQoA8P2RC3A4uPgJEZELg5pkYfCNzeCvUyOjyIyEswXeLg4RkWwwqEkW9BoVhndyXlO97vcLXi4NEZF8MKhJNkZ3d3Z/bzyagbJyu5dLQ0QkDwxqko3esaFoGWKAyWLDpkQuKUpEBPA2l1THqrpf9ZX3qlYqFRjXoyXe2Hoa/zuUjnu7R9dXMYmIZItBTXWqqvtVe7pX9X09orFk22kcSM1HWm4JWof51nURiYhkjUFNXlNZa1vdZTysofEY/vgC+Jz52eNrr2yNExE1Vgxq8prKWtt/Zhfjh+MXoWjTH/dPeRBqVcWpFJ5a40REjREnk5HsxIX5wl6cjzKrHcnZxd4uDhGRVzGoSXaUSgXMSTsAAEfPF3q3MEREXsagJlkqO7UbKoUCWUYLMo1mbxeHiMhrGNQkS8Jswg0RfgCA389xSVEiaroY1CRb3VoFAQCSs4thLLN6tzBERF7CoCbZauavR8sQA4QAfk8v9HZxiIi8gkFNstajVTAAIPFCEcqsXP+biJoeBjXJWqsQH4T76WBzCBxlq5qImiAGNcmaQqFAz9bOVvXv6YWwsFVNRE0Mg5pkr00zP4T6alFuc+A3tqqJqIlhUJPsKRQK9IoNAQAcOVcIM1vVRNSEMKipQWjTzA9hflqU2x1IOMvrqomo6WBQU4OgUChwa3woAOBIeiHsugAvl4iIqH4wqKnBiA31RXSQAXaHQFncQG8Xh4ioXjCoqcFQKBTod0MYAKA8sjOO8YYdRNQEMKipQYkI0OPGSH8AwIvrT8DhEF4uERFR3WJQU4PTt00YYLPgaHoh1iake7s4RER1ikFNDY6fTg2f1N0AgNd+OoWCknIvl4iIqO4wqKlB0l04jBsj/VFQasUrG054uzhERHWGQU0NkkI4sOi+LlAqgO+OZGBbUpa3i0REVCcY1NRgdW0ZhIf7xwEAXvjuOApL2QVORI0Pg5oatCeHtkVcmC+yjBY8v+44hOAscCJqXBjU1KDpNSq8NaEr1EoFfjyeyVngRNToMKipwesSHYSn72gHAHj5+yT8kWnycomIiGoPg5oahekD4tCvTRjKrHY8uuYwjGart4tERFQrGNTUKCiVCvx3Qle0CNQjNbcET/3vKFctI6JGgUFNjUaonw5LH+gBrUqJbSez8NrmU94uEhHRdWNQU6NyU8sg/GdMFwDAh7vO4IuD57xcIiKi68Ogpkbnnm5RmHX7DQCAud8lYvOJTC+XiIio5hjU1Cj9Y8gNGNMjGnaHwOOf/469f+Z6u0hERDXCoKZGSaFQYNG9nTG8YyTK7Q787ZNDDGsiapAY1NRoqVVK/Pf+rhjcLhxmqwP/t+oQfv4j29vFIiK6JmpvF4CoLunUKnzwYA889tlv2HYyG9M+SUCzcztgTt7n8fiI8DBs2ri+nkspP3eOGIWsnMp7IFhPRPWHQU2Nnk6twvuTeuCZr47i+6MZyIgejFsHjEHP1sFQKBRux346d6qXSikvWTm5eHD+ykr3s56I6g+DuoaqanGcSU2t59LQ1WjVSrw1visiA/VYtvsM9p3JQ26xBUM7RECjqp0RoKp+J9gCJaKaYlDXUFUtjrnj+9Vzaag6lEoFnr+rPdYsexfm9nchObsYOcUWDO8YiYgA/XWfv6rfCbZAiaimGNTUIKWkpKB7r74e912t9aq/eAR3TXoEPyVmorDUirUJ6egVG4qbY4LrqriNzvXUPxFdGwY1NUg2h+O6Wq9RQQZM6tUKO05lIzm7GPvO5CEtrwR2n7DaLmqjdL31T0TVx8uzqMnSa1S4s1Mk7ugQAa1KiYtFZhT1nIZ56xNRUFLu7eIREQFgi5oaoaq6ZQH3yX4KhQLtmwcgKsiA3ck5SMkpwSf7zuK7IxmYdfsNmNirFfQaVX0Um4jIIwY1NTpVdcsCnif7BRg0GNGlBVYsfhlRdz6KU5km/GtjEt7/OQVT+7bGA71jEGjQ1GWxiYg8Ytc30WU0hWfxwxP9sWB0Z0QFGZBbbMHrm/9An4Xb8erGJPyZXeztIhJRE8MWNdEVVEoFJvZqhbE3R2PjsQx88PMZ/JFlwvI9qVi+JxU3xwRjXM+WuLtzc/jq+L8QEdUt/pUhqoRGpcTobtG4p2sUfv4jB58dOIsdp7KRcLYACWcLMG/9CdzWvhlGdG6OQe2aebu4dcpmdyDbZEFmkRl5JeUIHPkcVu9Lg9nqgBACCoUCWrUSeo0Sxe1H4r2dfyI+3A/tm/ujVYhPhRXgyDu4NGzDxKAmugqFQoHBNzbD4BubIctoxteHz+OrhHSk5ZXih2MX8cOxi/DRqmDrMAp/ZhejdagP1LW02pk3ma12pOaW4M/sYpzNL4XdIaR92ubtUFBqdTu+zGpHURmAyM54ffMf0vbIAD16x4Xg1vhQ9G0Thuhgn/r6CHQFLg3bMDGoiS5TnYU8HhvcBjMHxeP4hSL8cOwiNh67iAuFZUBER/xw/CI0KgViw3zRNsIfMSENK7TtDoGf/8iGqcs4fPTLGVyWzfDRqtA8UI8wPx22frwAU2e/Cr1GBaVCAYcQKLc5UFJuwzcr30dgdFvYfUNh9w1HptGM745k4LsjGQCADs0DcEfHCNzRIRLtm/uztU10FQxqostUdyEPhUKBLtFB6BIdhOfuvBFHzxdhwrNvQNO2H0xmG05nFeN0VrEU2uVhbWG22mV7qVdRqRVfHU7H6n1ncS6/FAhtAwgg1FeL+GZ+aBPuhzA/rRSqG1MOVNoyLv5tA557dg8AwGp34GKRGRcKypBeUIqLhaVIumhE0kUj3tqWjOhgA+7oEIlhHSNwc+sQqJQMbaIrMaiJrpNCoUDXlkHwSdmBBx56AFlGC5KzTUjOLpZCG53HoMerW3F7+wjc1bk5BrULl0Vo/5Fpwqpf0/Dd7xdQZrUDAAINGlj++AXjxo1HsK/2us6vUSnRKsQHrUJ8cCtC8ckrM/HCWyuxJSkLu0/n4HxBGVbsTcWKvakI8dViSPtmGNYxEn3bhMmifojkgEFNVIsUCgUiA/WIDNSjX5swKbSPnD6LEgTi+6MZ+P5oBny1Kim0B7YNh0Fbf6FktTuwLSkLn+xLw/4z+dL2GyP9MaVPa9zTNQp9+7+CYN8Ha/29U08lYuFjEwAAPkoNNCGxKA9vB2toG+SXAGsTzmNtwnn4alUY1K4Z7ugYgcE3NkOAvuFdw86JW1RbGNREdeTy0E795J9Y8dVG/Hj8In48nokLhWVSaOs1Sgxq2wzDO0Vi8I3N6mxhlQuFZfjy4Dl8eSgdOSYLAOelaMM6RmDKra1xS2xInY8XVza0YHcIXCgsw48b1iO4Qz9kGs344fhFacy/Z+sQDGgbjoFtw3FjZMMY1+bELaotDGqiarqWpUmvpADQrVUwurUKxvN3tceR9EK30P7pRCZ+OpEJjUqBW+PDMLR9M9waH4b4cN/rCqWMwjJsOZGJLUlZ2H8mT5ocFuanw/ie0ZjUKwYtggw1Pn9tUSkVaBXiA9/kLfh19Us4dqEIm09kYvOJTJzJKcGvKXn4NSUPizadQjN/HQa0DUf/G8Jwa1womtXCLUqJ5IxBTVRNNVma1BOFQuEW2icyjNh8IhM/JWYiObsYu0/nYPfpHADOQO0dF4KuLYMQF+6LuDA/RAcbPM4kt9kdSC8owx+ZJvx+rgD7zuTh2Pkit2P6xIdiUq8YDO0QAa1anrPRlUrnmH/XlkF4dviNOJPjrJNdp3Ow/0w+sk0WfH34PL4+fB4A0DrUB7fEhuCW2FD0ig1BdLChQbS4iaqLQU1UD6pz2dfTd7RDSk4xNp/IxJ7kXBw+W4DcYgs2XroEzEWjUiDUVwd/vRpKhQI2hwNFZTYUlJa7XesMAAoF0KNVMIZ1jMSwjpFoFfrXTO2qxlCr6h2ob3HhfogL98P/Fv4D+rwCqANbwhoSB2twa9j9IpCWV4q0vFKsTXAGt8Jigtp0EWpTJlSmTKhNmWgeqOd4cB3ieHzdYlAT1YPqXvYVH+6HmYPaYOagNrDY7DiaXoT9Z/JwKtOIMzklSM0tgcXmQKbRjExjxXPpNUrEhfnhppaB6N4qGAPbhaOZv+eu4arGUKvbO1CfsnJyMfmK8lqsdmQUmfHlJx8hfuB9yDKa4dD5w6rzhzWsrXRckaUYDy4/gLgwX8SG+SI23A9RQQY0C9DBX6eulRa4ze6A2eaA2WqH2WqH3RCC/Eu3S1VI/3D+S61SwqHSwWZ31Ml19kIIlJTbkVdsQV5JOfKLy5FXYkFZq1uxOzkHZeV2lJXbYbbZYXcI2OwCNodASZ/H0XfRDqiUCqhVCvhq1Qjy0SDIR4sggwYRATpEBRsQFeSDqGADmgfooVQqOB5fxxjURF52tbHvy1sjDofARaMZ+cXlMFmsEAJQKhQIMKgR5qdDuJ8OygZ8LXJVdeGpla/TqBAb5ouSg19j3NP/gPXSUqc5JguyjWZkmyzILymH0Pnhl+Rc/JJcsdVn0Kicga1Xw0erhq9WBYNW5RbeDodAmfVSuFntzv+22lFW7pCeX9mbgd6P4tP9Zyv/sAOeRpsXNgEOGxR2KxR2K2C3QuEoh1YJ9OzWBQaNEgaNCgatGhqVc2EZhwCEcIaxQwiUltthNNtgLLPCaLbCWOb873K7o+J7xg/G7+cKKy+Tzt+5eE81ub4YFncYhYOp+Qj21SDER4sgHy2via9FDGoiL7va2PflrRGlUoGoIAOiZDABrC5UVRfVaeVrVMoK9WO1O/DpGy/hxQVv4ExuCVJzi5GaW4KLRWaYzDaUWe04m1daa58BAHRqJcrLSqAz+MIV3+LSPwScLVgp1pVqCKUaQvNXmcsAaZ7C9TBoVAjx1SLUT4sQXy1+/Xk7OvUaAINWBYNGBb1GBbVSAbVKCbVSgfefm4oZi1Y6vwQ4gHL7Xz0EB7d+hxH3TcCFgjJcKCzDxaIymK0OJF00AhEdse9MnvS+SgUQ7KOV3rs8zDmsU58r9TWm7ngGNRE1ahqVEhrjBYzr2bLCvrJyO7JNZuSYLCi22FBabkexxQaz1Q5xKUlfW7wEt4x4AGqVAhqV0vlvpfPfP70/D9+v/Qx6jQp6jRJ6jQpalRJKpQLde/Wt9EuHEAIvThqMFz7ZDqvdAZtdwGp3XHoIfLr4BYyd9S/nvktd03aHgEIBHNvxHWY+Mg0KhXNioo9WhQC9BgEGDQL0agQYNPDXqxHiq4WP1v1PfPcPnkT/B+6rtK7seemIrGQWfWLqbiweu1B67pq8+Gd2MZ6Y9x+07jcK+SXlyC8ph9UukFdSjrySciRnA+h8H25/Yxe0aiXiLi2v2zbCD20j/BEX7ouoIJ9aX0ugMXXHN6igTkxMxNSpU/Hnn39i2rRp+M9//sPZndSkVdVqOJ9+DtEtW1X6WjlNGKtr1ZnMV5n/XjiMm1r+3eO+s8f249677/C4r8rL9RQKwG5zdmt7WIGtPDUB7ZsHeHxt8oo9ePz21yo9d31Rq5TO8f4wXxjO7ccdHaYDcH4JMVlsyCt2hnZeiQWn//gD2tCWKLPacSrThFOZpgrnC/HVIjrYIPWIhPnrEGS4ND7uo0GwjxaBBg0MGhV0GqX0haguVPX/lTda4g0mqC0WC0aOHIlhw4bhyy+/xBNPPIFVq1Zh6tSG862IqLZdbUJYbVxO1hhUdzJfbZ63KdXv5RQKhbOFr9cgNswXAJD1+Rwk7NuD8wVlOJ1lwulsE5KzinE6y4SzeaUottik1viVlxRWRatSQqdWQqtWQqVUSA+1UoHCW6Zjzf6zUCic8ziu/LfxpgmYsuIg1Je9zvXalNDeaDO0H5SXei2UCuewk0apxPHt3+B0lgltI/zrqgoraDBBvWnTJhQVFWHJkiXw8fHBggUL8NhjjzGoqdG71glWdG2uZyGbpuR6fg9TUlJw862ev7hkp59Di9i2cOgD4NAHwqELdP63xgda30C07XQTCkutKCyzorC03O2ObuV2h3PSnMXDiX1DkXdp1r1HIXHYVdk8gOZdnGPvnsQPxqlMBrVHR48eRe/eveHj47wOtEuXLkhKSqr0eIvFAovlr59eUZHzW5rRWEnlXyO73QZzSbHHfUI4Kt13tf013eet1za088qxTFc7r9Vuw9g573jc9+rUO1iH13nequoXqHkd19VntdttNf47VtXfrau9b01/D6vz2vGzX/e478v5M7Bq0dbLyue8jMxic6Dcanf+2+5Auc0Bu8M5jm8XAnaHAzOeeBqDH3wSDiGcs+Th/LdDOCfy7f12JZ5/7lk4HAI2IeBwOOcD2B0C7yxdhptuv1c63jXb3mp34PRvexGu7VJrWeLvf/UlcRVCCFHlETLx9NNPw2w247333pO2hYeH4/Tp0wgODq5w/Msvv4xXXnmlPotIRER0TYqKihAQ4Hk+gkuDaVGr1WrodDq3bXq9HqWlpR6Des6cOXjqqaek5w6HA/n5+QgNDb3mCWhGoxEtW7ZEenr6VSuU/sJ6u3ass5phvV071tm1q4s68/e/ehd6gwnqkJAQJCYmum0zmUzQaj3fL1en01UI9qCgoOsqQ0BAAH+ha4D1du1YZzXDert2rLNrV991Js9V+T3o2bMn9u/fLz1PS0uDxWJBSEiIF0tFRERUtxpMUA8YMABFRUVYvXo1AGDRokUYMmQIVKravUieiIhIThpM17darcayZcswceJEzJ49G3a7Hbt27aqX99bpdJg3b16FrnSqGuvt2rHOaob1du1YZ9fOW3XWYGZ9u1y4cAEJCQno06cPwsPDvV0cIiKiOtXggpqIiKgpaTBj1ERERE0Rg5qIiEjGGNREREQyxqC+isTERPTs2RPBwcGYPXs2OKT/l/Xr1yMuLg5qtRq9evXCyZMnAVRdZ6zPvwwfPhyrVq0CwDqrrueeew4jR46UnrPeKvfpp5+iVatW8PPzw5AhQ5CWlgaAdeZJXl4eYmNjpToCal5PdVGHDOoquG6t2aNHDyQkJCApKUn6w9rUpaSkYOrUqVi0aBEuXLiAmJgYTJs2rco6Y33+5bPPPsPmzZsBVF0vrLO/JCYm4v3338dbb70FgPVWlZSUFLzwwgv47rvvkJSUhJiYGDz00EOsMw9yc3MxYsQIt5CuaT3VWR0KqtS6detEcHCwKCkpEUIIceTIEdG3b18vl0oeNmzYIJYuXSo937Fjh9BqtVXWGevTKS8vT0RERIh27dqJlStXss6qweFwiD59+ogXX3xR2sZ6q9xXX30lxo4dKz3/5ZdfRPPmzVlnHtx+++3irbfeEgBEamqqEKLmv1t1VYdsUVfhWm+t2ZSMGDECjz76qPT8jz/+QJs2baqsM9an09NPP43Ro0ejd+/eAKquF9aZ00cffYQjR44gNjYWGzduhNVqZb1VoUOHDtixYwd+//13FBUV4b333sPQoUNZZx4sW7YMs2bNcttW03qqqzpkUFfBaDQiNjZWeq5QKKBSqVBQUODFUslPeXk5Fi9ejJkzZ1ZZZ6xPYOfOndi+fTtee+01aRvrrGrFxcWYO3cubrjhBpw/fx5LlizBgAEDWG9V6NChA8aMGYPu3bsjKCgIBw4cwOLFi1lnHsTFxVXYVtN6qqs6ZFBXoapba9Jf5s6dCz8/PzzyyCNV1llTr0+z2Yzp06dj6dKlbnfeYZ1V7dtvv0VJSQl27NiBF198EVu2bEFhYSFWrFjBeqvE/v37sWHDBhw4cAAmkwn3338/7rrrLv6uVVNN66mu6pBBXYWQkBDk5OS4bavq1ppN0datW/HBBx/g888/h0ajqbLOmnp9vvrqq+jZsyfuvvtut+2ss6qdP38evXr1ku6Up1ar0aVLF5jNZtZbJf73v/9hwoQJuOWWW+Dn54f58+fjzJkz/F2rpprWU13VIYO6Cry1ZtXOnDmDSZMmYenSpejQoQOAquusqdfn559/jvXr1yMoKAhBQUH4/PPPMXPmTHzyySessyq0bNkSZWVlbtvOnj2LN954g/VWCZvNhqysLOm5yWRCSUkJ1Go166waavp3rM7q8LqnozViVqtVhIeHi08++UQIIcT06dPFiBEjvFwqeSgtLRXt27cXDz/8sDCZTNKjvLy80jpr6vWZnp4uUlNTpcd9990nXn/9dZGTk8M6q0JeXp4IDAwUS5cuFenp6eK///2v0Ol0Ijk5mfVWiS+++EIYDAaxZMkS8dlnn4nBgweLVq1a8f/PKuCyWd9V1UVN911X2a77DI3cunXrhMFgEM2aNROhoaEiMTHR20WShXXr1gkAFR6pqalV1hnr8y9TpkwRK1euFEJUXS+sMyH27dsn+vTpIwwGg4iNjRXr1q0TQrDeKuNwOMTLL78sWrVqJTQajejWrZtISEgQQrDOKnN5UAtR83qqizrk3bOqgbfWvHZV1Rnr0zPWWc2w3q4d66x6alpPtV2HDGoiIiIZ42QyIiIiGWNQExERyRiDmoiISMYY1ERERDLGoCZqZPLy8mrlPMXFxVc9xmq1YsGCBW5rGR84cACHDh2qlTJUR3p6+jUd3xRuNEGNC4OaqI6tX78evXr1qrDe7/nz56FQKCqsuuXJkCFD8O677171uMzMTMTExODYsWNu2yMiIvDNN99U+VqdToeTJ09Kz/v164cPPvigytfs3r0bS5YscVsi8cUXX8Tf//73Kl83YcIELF++XHqek5ODnj17orCwsMrXAcCePXtw6623wm63o7i4GF26dMHRo0ev+joAyMjIQKdOnbBnz55qHU8kB2pvF4CosVu+fDl69OgBnU4Hq9UKjUYDwLlYPwAYDAa34xMSErB06VLo9XooFAoAwJ9//ol169bh1KlT0nFWqxWPPvoounXrBuFcvAiRkZFYtGgRLl68iC5dukjHBgYGut0I5HKrVq3CyJEjERQUJJUlISEBFy5cwOTJk6/62WbMmAFfX18AzuA+deoU2rZti+XLl+Nvf/ubx9fp9Xq3mxesXLkSNpsNiYmJ0rYWLVp4vLORa810lUoFPz8/PPnkk/j73/+OXbt2Qal0b3uUlZVBo9FArXb+qfvoo4/Qv39/9OvXz+04IQSsVivUanWFcxB5G4OaqA6tX78eW7ZsQWRkJDZs2ICHHnoIffv2RWFhIUwmEwDgyy+/BOC8EcAdd9yBli1bYtKkSfDz85NC4+jRo+jfvz9GjBghnbu4uBgtWrQAAOzYsQN33XUXfH19oVQqYbfbYTKZ8M0332DUqFHQarXSF4TLZWVl4bHHHsO4ceOgUChgt9tht9vx8ssvw8/PD35+fmjTpg2Sk5MRFRWFqKgoHDhwAIBzHeOvv/5aar0bjUY8+uij+OSTT9ChQwfceuut8PPzw/jx46X3s1gsbu9fXl4Os9mMJUuWoGvXrlILft26dfj2228rBPWPP/6IAwcOYM2aNdK2p59+GitXrsScOXPcbh8KAEFBQdBqtdBqtbDb7SgqKkJoaCjCwsI8/ry2b9+Om266yeM+Iq+57rXNiMijxMREERAQINauXeu2vUePHuLRRx8Vr7zyigAgXn/9dTFt2jTRp08f6Zjp06eL1q1bi/j4eBEfHy98fHxEs2bNpOcxMTFiwoQJlb73M888I3r37i0979ixo9i5c2eF4/bs2SN8fHxETEyMUCqVIjIyUowdO1a0bdtWpKWliejoaJGSkiJCQkLEZ599Ju68807ptWPGjJGWXSwoKBD9+vUTzz//vLQ/KSlJNG/eXMycOVPk5uYKIYSYM2eOaNmypVAqlaJZs2aiT58+4uGHHxbt27cX999/vxBCiK1bt4qbb765Qlnz8/NFixYtxDvvvFNh34EDB4Sfn5948sknhdVq9VgnM2bMEJMmTRJCCDFy5EixdevWSuuPSE4Y1ER15OzZs+KTTz4R7dq1kwL2wIEDolevXmLnzp0iJydHuL4rb9q0SQwcOFB6bXl5uXA4HNLzu+++W1oXXAghbDabsFgsHt937969wmAwiCNHjkjbKgvqV155RTz33HNCCCEiIiJEamqqmDVrlti4caNYtWqVGDt2rNi+fbvo2LGjWLp0qXjggQeEEEKsWbNGtGjRQrRs2VLs27dPxMXFieeff14kJCQIu90uhBDi1KlTYsuWLaJ3795i5syZ0nteuHBBKBQKsXTpUpGfny9mzZoliouLxcSJE8Uzzzwj2rZtK06ePOlWzrKyMjF48GAxbNiwSoP4wIEDIjw8XNx0003SutYu69atEx06dBBFRUVCCCFuvfVWsWXLFo/nIZIbdn0T1ZFWrVph8uTJuOWWWzB8+HCkpaVd9TXr16/HP/7xD6hUKrftFy9exKFDhzB//nxpm8PhgNlsRmJionQbvZSUFNx777144oknYLVaq1XOu+66y+35W2+9BQDo27cvnn32WSQnJ+OGG26A0WiEn58fAODXX3/FO++8g+effx6RkZFYsWIFevTogcDAQFgsFiiVSixbtgxarRZ79+6FzWaTzr98+XKoVCq8+eabyMrKwltvvQWz2Yzu3btj8eLFiIyMRHZ2Ntq1ayeN0T/11FPIycnBkCFDPHbhuxw4cADPPPOM2+S2nTt3YuLEiVAoFFJXelFREcaMGeN2rrNnz0pj7URywqAmqkNffPEFjh49CqPRiNdffx3t27ev8vhhw4bht99+Q0BAAFQqFbZt24bx48fju+++w6FDh/D8888DcE4ucx0TFBQEwDkb+r777oPNZkNYWBiGDx+O559/Hk899VSl7/fSSy8BcN6/2OFw4PXXX0dISAji4uJQUlKCESNG4IEHHkDv3r1hNBqlIHvvvfcAQCrPwIEDUVBQgIiICGnilkajgVarhVKplILTaDRi1apVGDFiBO644w6cOnUKEyZMwJkzZzBlyhScPXsWf/75J1599VVMnDgRc+bMwWOPPYbXXnsNpaWlCAwMxPz58/H888+jvLwcb775JgDnF5Ru3brh5ptvxu7du6XPt3LlSjz55JN48MEHkZWVhe+++w6Ac0b7yy+/jCFDhsBms7lNOCOSG05vJKpDDocDDocDgHNmscuECRPQvXt3AEDr1q0xZcoUAM7Z0MHBwVCpVFixYgVGjBiBl156CbfddhuWL1+O33//HdnZ2bjzzjsxd+5chIaGQqlU4r///S8GDx6M559/HkOHDkVYWBg++eQTqbVamXfeeQcDBgxA69atUVBQgJiYGERFReGJJ57Ae++9h6KiImzYsAFjxoyB0WiEj49PpecyGo1o1qyZ2zZXi9hl7ty5mDJlCgIDA+Hv74+XX34Z48aNQ0lJCZYuXYru3btj3LhxOH78OGbOnImJEycCAPz9/REREQG9Xg9fX18kJiaie/fu0Ov10Ov1yMvLQ4sWLdxmbJ8+fRqvvPIK1q1bh8GDB1/1Z3VlLwaRXPArJFEdmjRpEnr06IG1a9fin//8JwDgmWeewZdffolOnTohPDwcaWlp+OmnnzBv3jwAztbhk08+iZMnT6JTp04IDAyESqXCvHnzMGXKFFgsFowfPx6vvvqq9D5jx45FXFwcRo4ciX379gEA7r77bhw5ckS6DMyTm266CW3atMEdd9yBqKgojBs3Dn5+fmjZsiX69u2Lxx57DPfddx/i4+NhNBqlWeae/PHHH2jVqlWl+4UQsNvtePrpp/HYY48BAIKDg9G3b18kJSW5fZF56KGHoFAoEBwcXOE858+fx/79+7Fq1SppW0ZGBqKjo92Oa9u2LVJSUqBSqaSZ9UQNEYOaqI45HA4IIfDaa68hICBAuhY6NzdXOmb48OEYPnw48vPz0a9fP4waNQpr1qzBI488AgA4duwYzp8/j65du2L37t1SkLm0aNHCY4i6xq4vl5aWho8//hhz587FgAEDKuwPCwvD3XffjaVLl2Lz5s04ePAgAKCwsBD+/v6Vfs5ly5Zh0KBBle5XKBRSl/nlKrtu+crWOACYzWb87W9/w+TJk9GyZUtpe0ZGhttzF1crubLx+t9++w27du2CwWBgi5pki13fRHXs119/xblz53D48GHcf//90na73Q4AUtc44AzWP//8Ex988AECAgJQWlqK999/H/369YPNZsOKFStw//33o1OnTrj55psxbdq0Ckt9lpeXu50TcAaWa6nNn3/+Ge+8806FMVmz2QybzYbk5GRMmDABS5YswZYtW7Bt2zYsW7YMu3fvRtu2bSu8xuFw4I033sD+/fvdFji5vNv/Spe3nl3HdOrUSXqsX7++wmtTUlIwdOhQlJSU4D//+Q8A5yS7vXv3Yu3atVWO/2u1Wrdrp61WK6xWK9LT07F8+XIsXLjQ4xcDIjlgUBPVsR49euCtt97C2rVrpYlfAKSx4yvHkC+feewa9z1x4gReeuklqNVqLFy4UJrd7VqU5HLZ2dkVliUdMGAA/u///g++vr6YPn06nn322QpBXVxcDLPZjKCgIMTFxSEhIQFxcXFITU3FL7/8gqVLl2Lo0KFurykvL0dGRgbWrFmDb775BoGBgdI+i8VS6fKoNptNauW6FkFJTEyUHqNGjXJrBZ86dQpdu3ZF+/bt8dNPP0kt+6KiIowfPx433HADZs6c6fG9AGD8+PH4+OOPpedWqxUWiwWjRo1CYmIiZs2aVelribxNIS7/aktEslJUVISAgADZt/aEENdUxvz8fOh0Ovj6+kIIgZKSkgpfOK6UnZ1dYbIaUVPAoCYiIpIxdn0TERHJGIOaiIhIxhjUREREMsagJiIikjEGNRERkYwxqImIiGSMQU1ERCRjDGoiIiIZ+/9n0B2RzKlRkwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "watch1 = watches_gifts[(watches_gifts.shipping_limit_date>'2018-06-01')&(watches_gifts.shipping_limit_date<'2018-09-01')]\n",
    "#获取2018Q3季度钟表礼物数据\n",
    "watch2 = watches_gifts[(watches_gifts.shipping_limit_date<'2018-06-01')&(watches_gifts.shipping_limit_date>'2018-03-01')]\n",
    "#获取2018Q2季度钟表礼物数据\n",
    "sns.displot(watch1[watch1.price<1000].price,kde = True)\n",
    "plt.title('2018年Q3季度钟表礼物销售情况')\n",
    "plt.xlabel('钟表礼物价格分布')\n",
    "plt.ylabel('订单量')\n",
    "plt.title('2018年Q2季度钟表礼物销售情况')\n",
    "plt.xlabel('钟表礼物价格分布')\n",
    "plt.ylabel('订单量')\n",
    "sns.displot(watch2[watch2.price<1000].price,kde = True)\n",
    "plt.title('2018年Q2季度钟表礼物销售情况')\n",
    "plt.xlabel('钟表礼物价格分布')\n",
    "plt.ylabel('订单量')\n",
    "plt.show()\n",
    "#sns函数绘制立方分布图"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66cea1a5-e4e1-4e30-a94a-84d92c68096d",
   "metadata": {},
   "source": [
    "**结论：2018Q3的钟表礼物平均价格区间在[0,100]，而Q2的价格区间主要集中在[100,150]。即Q3季度客户倾向于购买低于100元以内的商品，而Q2季度偏爱100-150元区间的价格商品。**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "83d0c0ed-c222-48b8-b4b4-84a26d5ffbc5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "钟表礼物各月份订单数量如下：\n",
      "year_month\n",
      "2016-10      5\n",
      "2017-01      7\n",
      "2017-02     24\n",
      "2017-03     87\n",
      "2017-04     81\n",
      "2017-05    136\n",
      "2017-06    135\n",
      "2017-07    141\n",
      "2017-08    221\n",
      "2017-09    246\n",
      "2017-10    316\n",
      "2017-11    437\n",
      "2017-12    400\n",
      "2018-01    344\n",
      "2018-02    331\n",
      "2018-03    453\n",
      "2018-04    394\n",
      "2018-05    741\n",
      "2018-06    498\n",
      "2018-07    496\n",
      "2018-08    503\n",
      "2018-09      5\n",
      "Freq: M, Name: order_id, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "orders_number = watches_gifts.groupby('year_month')['order_id'].count()\n",
    "#统计钟表礼物每个的订单数量\n",
    "print('钟表礼物各月份订单数量如下：')\n",
    "print(orders_number)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f926dfcd-3ed7-4f19-9975-4ebafcd16509",
   "metadata": {},
   "source": [
    "2018年Q2季度平均订单量为529，其中5月出现爆单；2018年Q3季度平均订单量为499，订单量总体平稳。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "13fc9538-68d6-4437-a791-4edc1df989f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2018年5月爆单商品id和订单数如下：\n",
      "product_id\n",
      "a92930c327948861c015c919a0bcb4a8    111\n",
      "Name: count, dtype: int64\n",
      "--------------------分割线--------------------\n",
      "2018年Q3季度热销商品id和订单数如下：\n",
      "product_id\n",
      "53b36df67ebb7c41585e8d54d6772e08    235\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "the_popular_product_1 = watch1['product_id'].value_counts().head(1)\n",
    "#获取爆单商品信息\n",
    "print('2018年5月爆单商品id和订单数如下：')\n",
    "print(the_popular_product_1)\n",
    "print('--------------------分割线--------------------')\n",
    "the_popular_product_2 = watch2['product_id'].value_counts().head(1)\n",
    "#获取热销商品信息\n",
    "print('2018年Q3季度热销商品id和订单数如下：')\n",
    "print(the_popular_product_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "f90c6c58-85a7-4920-b75f-7683a15a1b85",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2018年5月爆单商品均价如下：\n",
      "77.95495495495496\n",
      "--------------------分割线--------------------\n",
      "2018年Q3季度商品均价如下：\n",
      "106.66731914893619\n"
     ]
    }
   ],
   "source": [
    "the_popular_product_1_average_price = watch1[watch1['product_id']=='a92930c327948861c015c919a0bcb4a8'].price.mean()\n",
    "#计算爆单商品均价\n",
    "print('2018年5月爆单商品均价如下：')\n",
    "print(the_popular_product_1_average_price)\n",
    "the_popular_product_2_average_price = watch2[watch2['product_id']=='53b36df67ebb7c41585e8d54d6772e08'].price.mean()\n",
    "print('--------------------分割线--------------------')\n",
    "#计算热销商品均价\n",
    "print('2018年Q3季度商品均价如下：')\n",
    "print(the_popular_product_2_average_price)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51d7a8b4-a63b-4158-88af-91317ebe888f",
   "metadata": {},
   "source": [
    "2018年Q2季度爆单产品（id:a92930c327948861c015c919a0bcb4a8）和2018年Q3季度热销产品（id:53b36df67ebb7c41585e8d54d6772e08），均价为80和107元，可重点关注这两种商品。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25579452-88ca-4c03-ae3e-ea73cac393bb",
   "metadata": {},
   "source": [
    "**结论：基于2018年Q3季度相较于2018年Q2季度客单价呈现下降趋势，因此假设1成立。与此同时，2018年Q3季度订单相比于Q2也呈现下降趋势。**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f7d2765-c433-47bb-b539-f31c37823c8b",
   "metadata": {},
   "source": [
    "#### **假设2：产品质量存在问题**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "6f3fb9df-e2ec-4125-97ff-081b4fa8f5fe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "钟表礼物各月份订单评价如下：\n",
      "year_month\n",
      "2016-10    4.000000\n",
      "2017-01    3.714286\n",
      "2017-02    4.500000\n",
      "2017-03    4.104651\n",
      "2017-04    3.790123\n",
      "2017-05    4.198529\n",
      "2017-06    4.165414\n",
      "2017-07    4.106383\n",
      "2017-08    4.272727\n",
      "2017-09    4.221311\n",
      "2017-10    4.133758\n",
      "2017-11    3.918415\n",
      "2017-12    4.035354\n",
      "2018-01    3.887906\n",
      "2018-02    3.743202\n",
      "2018-03    3.509091\n",
      "2018-04    4.173469\n",
      "2018-05    4.069012\n",
      "2018-06    4.137097\n",
      "2018-07    3.973415\n",
      "2018-08    4.155070\n",
      "2018-09    4.000000\n",
      "Freq: M, Name: review_score, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "watches_average_review = watches_gifts.groupby('year_month')['review_score'].mean()\n",
    "#计算各月份钟表礼物订单评价均分\n",
    "print('钟表礼物各月份订单评价如下：')\n",
    "print(watches_average_review)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "d0bf0723-c076-4ac9-b837-372ac1314a87",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2018年Q2季度钟表礼物订单数量为70.0，而2018年Q2季度钟表礼物订单数量为为97.0\n"
     ]
    }
   ],
   "source": [
    "watches_bad_review1 = watch1[(watch1.review_score==1)|( watch1.review_score==2)]\n",
    "average_review1 = round(watches_bad_review1.order_id.count()/3,0)\n",
    "watches_bad_review2 = watch2[(watch2.review_score==1)|( watch2.review_score==2)]\n",
    "average_review2 = round(watches_bad_review2.order_id.count()/3,0)\n",
    "print(f'2018年Q2季度钟表礼物差评订单数：：{average_review1}，而2018年Q2季度钟表礼物差评订单数：：{average_review2}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a8baa56-cbd2-48df-b251-07dd505aa2f0",
   "metadata": {},
   "source": [
    "**结论：2018Q2季度钟表礼物订单评价为3.91分（3.5+4.17+4.06/3），Q3季度为4.08分（4.13+3.97+4.15/3），而且差评（订单评价为1星和2星）订单数量分别为70和97，差评占比为14%和19%。因此不存在严重商品质量问题，假设2不成立。**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14c77d8f-cc5b-41d4-a634-7866bdb44437",
   "metadata": {},
   "source": [
    "#### **假设3：付费客户人数下降**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "524f1db7-495e-4254-9e0d-0d91a674231e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2018年Q3季度下单人数如下：\n",
      "year_month\n",
      "2018-06    498\n",
      "2018-07    496\n",
      "2018-08    503\n",
      "Freq: M, Name: customer_id, dtype: int64\n",
      "--------------------分割线--------------------\n",
      "2018年Q2季度下单人数如下：\n",
      "year_month\n",
      "2018-03    453\n",
      "2018-04    394\n",
      "2018-05    741\n",
      "Freq: M, Name: customer_id, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "customers_number1 = watch1.groupby('year_month')['customer_id'].count()\n",
    "print('2018年Q3季度下单人数如下：')\n",
    "print(customers_number1)\n",
    "print('--------------------分割线--------------------')\n",
    "customers_number2 = watch2.groupby('year_month')['customer_id'].count()\n",
    "print('2018年Q2季度下单人数如下：')\n",
    "print(customers_number2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ed16e41-0b09-476d-9067-2dc2105665ba",
   "metadata": {},
   "source": [
    "#### **2018年5月付费客户人数（741人）月环比增长88%，相比于6月（498人）环比减少33%。**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "e68fccd9-fe1e-423f-bc36-e7d6414261f1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2018年Q3季度新、老用户人数如下：\n",
      "is_new      True\n",
      "year_month      \n",
      "2018-06      459\n",
      "2018-07      484\n",
      "2018-08      477\n",
      "--------------------分割线--------------------\n",
      "2018年Q2季度新、老用户人数如下：\n",
      "is_new      True\n",
      "year_month      \n",
      "2018-03      437\n",
      "2018-04      377\n",
      "2018-05      688\n"
     ]
    }
   ],
   "source": [
    "first_orders = df.groupby('customer_id')['year_month'].min()\n",
    "#定义first_orders来标记是否为新用户\n",
    "df['first_order_month'] = df['customer_id'].map(first_orders)\n",
    "#增加[first_order_month]列与客户id绑定\n",
    "df['is_new'] = df['year_month']==df['first_order_month']\n",
    "#增加[is_new]列标记客户是否为用户\n",
    "watches_gifts = df[df['product_category_name_english']=='watches_gifts']\n",
    "#获取包含钟表礼物类的数据框架\n",
    "watch1 = watches_gifts[(watches_gifts.shipping_limit_date>'2018-06-01')&(watches_gifts.shipping_limit_date<'2018-09-01')]\n",
    "#获取2018Q3季度钟表礼物数据\n",
    "watch2 = watches_gifts[(watches_gifts.shipping_limit_date<'2018-06-01')&(watches_gifts.shipping_limit_date>'2018-03-01')]\n",
    "#获取2018Q2季度钟表礼物数据\n",
    "watch1_monthly_new_old = watch1.groupby(['year_month', 'is_new'])['customer_id'].nunique().unstack().fillna(0)\n",
    "#2018年Q3新、老用户人数（Truew为新用户，False为老用户）\n",
    "watch2_monthly_new_old = watch2.groupby(['year_month', 'is_new'])['customer_id'].nunique().unstack().fillna(0)\n",
    "#2018年Q2新、老用户人数（Truew为新用户，False为老用户）\n",
    "print('2018年Q3季度新、老用户人数如下：')\n",
    "print(watch1_monthly_new_old)\n",
    "print('--------------------分割线--------------------')\n",
    "print('2018年Q2季度新、老用户人数如下：')\n",
    "print(watch2_monthly_new_old)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf2006a2-bba5-4ef6-bc46-b3447e0856bb",
   "metadata": {},
   "source": [
    "#### **结论：2018Q2钟表礼物新用户付款人数大幅度下降，5月有688位新用户，6月份只有459位，而且Q2和Q3均无老用户下单，因此假设3正确。**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78dabbb9-1145-4cde-8028-8d5f33868d5c",
   "metadata": {},
   "source": [
    "#### **假设4：转化率下降**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "8c4173ba-5a66-48ba-a7cb-fcaef2ecd7d1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2018年Q3钟表礼物类商品取消订单量：0\n",
      "2018年Q2钟表礼物类商品取消订单量：2\n"
     ]
    }
   ],
   "source": [
    "watch1_gifts_canceled = watch1[watch1['order_status']=='canceled']\n",
    "watch2_gifts_canceled = watch2[watch2['order_status']=='canceled']\n",
    "print(f'2018年Q3钟表礼物类商品取消订单量：{watch1_gifts_canceled.order_id.count()}')\n",
    "print(f'2018年Q2钟表礼物类商品取消订单量：{watch2_gifts_canceled.order_id.count()}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6aa4b181-1f33-4576-b89e-f48b58e97c95",
   "metadata": {},
   "source": [
    "#### 结论：两个季度取消订单量占比不足总订单的1%，因此假设4不成立"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7fec9597-4e2e-4640-8fb6-a3a8ef464ffb",
   "metadata": {},
   "source": [
    "### **综上所述，2018年Q3季度钟表礼物销售额下降原因是客户消费能力下降、新用户下单人数减少共同导致。**"
   ]
  }
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